Triple
T7034665
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hjalmar |
E163350
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Hjalmar Wijk
Hjalmar Wijk was a Swedish politician and public figure active in the early 20th century.
|
E652832
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Hjalmar Wijk | Statement: [Hjalmar, hasNotableBearer, Hjalmar Wijk]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hjalmar Wijk Context triple: [Hjalmar, hasNotableBearer, Hjalmar Wijk]
-
A.
Hjalmar Lundbohm
Hjalmar Lundbohm was a Swedish geologist and mining engineer best known as the first managing director of LKAB and a key figure in the development of the mining town of Kiruna.
-
B.
Hjalmar Pettersson
Hjalmar Pettersson is a person notable for bearing the Scandinavian given name Hjalmar.
-
C.
Hjalmar Mehr
Hjalmar Mehr was a prominent Swedish Social Democratic politician who served as mayor of Stockholm and played a key role in the city’s postwar urban redevelopment.
-
D.
Hjalmar Carlsson
Hjalmar Carlsson is a personal name bearer of the given name Hjalmar, likely of Scandinavian origin.
-
E.
Hjalmar Welhaven
Hjalmar Welhaven was a Norwegian architect and cultural figure known for his contributions to 19th-century Norwegian architecture and his connections to prominent literary and artistic circles.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Hjalmar Wijk Triple: [Hjalmar, hasNotableBearer, Hjalmar Wijk]
Generated description
Hjalmar Wijk was a Swedish politician and public figure active in the early 20th century.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hjalmar Wijk Target entity description: Hjalmar Wijk was a Swedish politician and public figure active in the early 20th century.
-
A.
Hjalmar Lundbohm
Hjalmar Lundbohm was a Swedish geologist and mining engineer best known as the first managing director of LKAB and a key figure in the development of the mining town of Kiruna.
-
B.
Hjalmar Pettersson
Hjalmar Pettersson is a person notable for bearing the Scandinavian given name Hjalmar.
-
C.
Hjalmar Mehr
Hjalmar Mehr was a prominent Swedish Social Democratic politician who served as mayor of Stockholm and played a key role in the city’s postwar urban redevelopment.
-
D.
Hjalmar Carlsson
Hjalmar Carlsson is a personal name bearer of the given name Hjalmar, likely of Scandinavian origin.
-
E.
Hjalmar Welhaven
Hjalmar Welhaven was a Norwegian architect and cultural figure known for his contributions to 19th-century Norwegian architecture and his connections to prominent literary and artistic circles.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69c6885d691c81908cf7d31083113886 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6e212e28c8190bf38ce9a25d2032e |
completed | March 27, 2026, 8:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7dafcc8b4819080c962d109381a69 |
completed | March 28, 2026, 1:43 p.m. |
| NEDg | Description generation | batch_69c7dbd350a08190aa34ada9ba8d39ce |
completed | March 28, 2026, 1:46 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c7dc7cb2d48190a40523eb7b03a9ef |
completed | March 28, 2026, 1:49 p.m. |
Created at: March 27, 2026, 2:36 p.m.